Microsoft Brings Collaboration To New Office Tool SwayFreestyle Capital, a venture shop based in California, has locked down a $60 million third fund. The new infusion brings the firm’s total capital raised to $126 million. In addition to its new traunch, Freestyle has brought Jenny Lefcourt into its ranks as its third partner.
Showing posts with label Capital. Show all posts
Showing posts with label Capital. Show all posts
Thursday, 2 April 2015
Thursday, 12 March 2015
Passion Capital Backs Ravelin’s Hybrid Approach To Tackling Online Fraud
Google Brings Street View To Mount Everest Region
Another fintech investment to chalk up in London: Passion Capital has invested an undisclosed level of seed funding in Ravelin, an early stage online fraud prevention startup formed by a team of ex-Hailo employees in January this year. The startup is currently working out of Passion’s co-working space, White Bear Yard.
Ravelin’s founders had been involved in fraud prevention at the taxi app, among other roles, where they came up with the original idea to spin out their own business. The seed funding will be used to get their platform to market later this year.
Passion’s average seed round investment — last we crunched the numbers — was around £187,300. TechCrunch understands that in Ravelin’s case the VC is investing above that average. Albeit the sums involved here are clearly modest at this nascent stage. Ravelin is currently working with a small group of beta customers as it develops the platform for a full launch, pegged for Q4.
“We’re starting beta development with our four confirmed beta partners. We have a long list which we’re introducing gradually so as not to swamp our development team. And we expect by the end of summer to have a working product that’s in production with those guys, and then we’re going to go through a hardening process with the actual product and build up our marketing and sales team before we take it to market at the end of the year,” says co-founder and CEO Martin Sweeney.
Ravelin is competing with well-financed online fraud prevention startups, such as U.S.-based Sift Science, which has pulled in some $23 million in VC funding thus far. However it’s not just a less flush U.K. clone. The spin here is it’s not taking a pure-play machine learning route to tackle online card fraud. Rather it’s setting itself up as hybrid platform that blends human agency and machine learning smarts — looping in some algorithmic fraud detection but also not requiring businesses to abandon existing human-oversight and processes. So its a stepping stone sales pitch, for those not ready to fully embrace robotic overlords.
“If you look around in the market you’ve got the established [fraud prevention] players, who’ve been around for 10 or 15 years, who’ve all been bought by big payment processors like AmEx or Visa, and then at the other end of the scale you’ve got new entrants who are doing very much pure-play machine learning. And what we’ve found by talking to people — real world companies — is that neither are particularly serving their needs,” Sweeney tells TechCrunch.
“It’s very hard to go into a company and say ‘look guys, all of that expertise you’ve built up over your lifetime as a company is no longer relevant and your team’s experience is defunct because this new technology replaces it. But also it’s quite hard to go in and say the same tools you’ve been using for the past 10 years are going to be up to date with the changing face of fraud.”
Omnichannel retailing means mobile commerce is proliferating, and more and more browsers and payment methods are being looped into the mix. It’s generally an increasingly complex landscape to monitor when it comes to fraud prevention. So that means human oversight is being strained — but that does not mean it should be replaced entirely, argues Sweeney.
“The old stuff doesn’t work, but the new stuff doesn’t address that fact that these people know what they are doing. So we’re aiming to sit directly in between those two positions,” he adds.
What does that mean in practice? Ravelin will offer access to an aggregated dashboard for fraud analysts that’s pitched as easier to use and more comprehensive than existing offerings, and which also leverages machine learning and social graph information to aid fraud detection — but as a supplementary signal which the humans who oversee fraud prevention in-house can choose how they respond to.
“We’re really trying to increase the efficiency and empower the human beings who are the core of the fraud prevention set up in any established company,” he continues. “What we try to do is to use new technology, including machine learning and social graph and graph network analysis to make their lives easier and make their jobs more efficient.
“These guys already have dashboards that they use, but they tend to be quite hard to use. And they have disparate sources of information. So we’re combining all of that information into once place in the dashboard for the analysts to use. We also provide ways for usually the manager of those analysts, the actual head of fraud, to keep on top of the numbers. To understand exactly what’s happening. To have a lot more control over what you would in the industry call a false positive.”
Sweeney says this approach allows for businesses to set their own risk appetite and continue making their own decisions on whether they want to review all transactions or let them all go through automatically.
“They can still define the rules themselves for what makes fraud, rather than relying on the machine learning — which does the easy stuff but doesn’t take into account all of their expertise. So it’s combining machine learning with some of the more traditional fraud techniques that these people are used to,” he adds.
“People don’t really trust [AI]. It’s not being around long enough to say I trust my job and my responsibility to this computer. They still want some oversight and what we’re doing is we’re aiming to give them all the benefits of these new technologies but without making it seem and feel too risky. We don’t want to make them feel like their jobs are at risk, and they’re putting their teams out of business. We’re just making their jobs more efficient.”
Ravelin will be targeting the platform at SMEs — or “large scale companies who are tech savvy”, as Sweeney puts it. Its business model is software as a service, following the established industry model of charging a per transaction fee, with the exact level based on volumes, albeit aiming to slightly undercut the industry average.
It’s using the new seed financing to fund its beta development process, likely to last six months, shaping the platform in conjunction with its first set of customers to ensure it hits a spectrum of ecommerce businesses’ needs.
“Having come from the taxi industry, we know everything there is about fraud in the taxi industry but not so much about for instance gaming, gambling, retail and all the other different arenas that ecommerce touches these days,” adds Sweeney. “Not just people who sell goods, but people who sell services as well. Because that’s an increasing area that fraud is touching.
“People who sell services are just as exposed there days because of the prevalence of stolen credit card data. And the quality of identity information you can buy on the dark net. Because of all the leaks that have happened, and all the hacking attacks — even the ones you don’t hear about. There’s a huge amount of high quality information out there which is just really hard to track.”
Another fintech investment to chalk up in London: Passion Capital has invested an undisclosed level of seed funding in Ravelin, an early stage online fraud prevention startup formed by a team of ex-Hailo employees in January this year. The startup is currently working out of Passion’s co-working space, White Bear Yard.Ravelin’s founders had been involved in fraud prevention at the taxi app, among other roles, where they came up with the original idea to spin out their own business. The seed funding will be used to get their platform to market later this year.
Passion’s average seed round investment — last we crunched the numbers — was around £187,300. TechCrunch understands that in Ravelin’s case the VC is investing above that average. Albeit the sums involved here are clearly modest at this nascent stage. Ravelin is currently working with a small group of beta customers as it develops the platform for a full launch, pegged for Q4.
“We’re starting beta development with our four confirmed beta partners. We have a long list which we’re introducing gradually so as not to swamp our development team. And we expect by the end of summer to have a working product that’s in production with those guys, and then we’re going to go through a hardening process with the actual product and build up our marketing and sales team before we take it to market at the end of the year,” says co-founder and CEO Martin Sweeney.
Ravelin is competing with well-financed online fraud prevention startups, such as U.S.-based Sift Science, which has pulled in some $23 million in VC funding thus far. However it’s not just a less flush U.K. clone. The spin here is it’s not taking a pure-play machine learning route to tackle online card fraud. Rather it’s setting itself up as hybrid platform that blends human agency and machine learning smarts — looping in some algorithmic fraud detection but also not requiring businesses to abandon existing human-oversight and processes. So its a stepping stone sales pitch, for those not ready to fully embrace robotic overlords.
“If you look around in the market you’ve got the established [fraud prevention] players, who’ve been around for 10 or 15 years, who’ve all been bought by big payment processors like AmEx or Visa, and then at the other end of the scale you’ve got new entrants who are doing very much pure-play machine learning. And what we’ve found by talking to people — real world companies — is that neither are particularly serving their needs,” Sweeney tells TechCrunch.
“It’s very hard to go into a company and say ‘look guys, all of that expertise you’ve built up over your lifetime as a company is no longer relevant and your team’s experience is defunct because this new technology replaces it. But also it’s quite hard to go in and say the same tools you’ve been using for the past 10 years are going to be up to date with the changing face of fraud.”
Omnichannel retailing means mobile commerce is proliferating, and more and more browsers and payment methods are being looped into the mix. It’s generally an increasingly complex landscape to monitor when it comes to fraud prevention. So that means human oversight is being strained — but that does not mean it should be replaced entirely, argues Sweeney.
“The old stuff doesn’t work, but the new stuff doesn’t address that fact that these people know what they are doing. So we’re aiming to sit directly in between those two positions,” he adds.
What does that mean in practice? Ravelin will offer access to an aggregated dashboard for fraud analysts that’s pitched as easier to use and more comprehensive than existing offerings, and which also leverages machine learning and social graph information to aid fraud detection — but as a supplementary signal which the humans who oversee fraud prevention in-house can choose how they respond to.
“We’re really trying to increase the efficiency and empower the human beings who are the core of the fraud prevention set up in any established company,” he continues. “What we try to do is to use new technology, including machine learning and social graph and graph network analysis to make their lives easier and make their jobs more efficient.
“These guys already have dashboards that they use, but they tend to be quite hard to use. And they have disparate sources of information. So we’re combining all of that information into once place in the dashboard for the analysts to use. We also provide ways for usually the manager of those analysts, the actual head of fraud, to keep on top of the numbers. To understand exactly what’s happening. To have a lot more control over what you would in the industry call a false positive.”
Sweeney says this approach allows for businesses to set their own risk appetite and continue making their own decisions on whether they want to review all transactions or let them all go through automatically.
“They can still define the rules themselves for what makes fraud, rather than relying on the machine learning — which does the easy stuff but doesn’t take into account all of their expertise. So it’s combining machine learning with some of the more traditional fraud techniques that these people are used to,” he adds.
“People don’t really trust [AI]. It’s not being around long enough to say I trust my job and my responsibility to this computer. They still want some oversight and what we’re doing is we’re aiming to give them all the benefits of these new technologies but without making it seem and feel too risky. We don’t want to make them feel like their jobs are at risk, and they’re putting their teams out of business. We’re just making their jobs more efficient.”
Ravelin will be targeting the platform at SMEs — or “large scale companies who are tech savvy”, as Sweeney puts it. Its business model is software as a service, following the established industry model of charging a per transaction fee, with the exact level based on volumes, albeit aiming to slightly undercut the industry average.
It’s using the new seed financing to fund its beta development process, likely to last six months, shaping the platform in conjunction with its first set of customers to ensure it hits a spectrum of ecommerce businesses’ needs.
“Having come from the taxi industry, we know everything there is about fraud in the taxi industry but not so much about for instance gaming, gambling, retail and all the other different arenas that ecommerce touches these days,” adds Sweeney. “Not just people who sell goods, but people who sell services as well. Because that’s an increasing area that fraud is touching.
“People who sell services are just as exposed there days because of the prevalence of stolen credit card data. And the quality of identity information you can buy on the dark net. Because of all the leaks that have happened, and all the hacking attacks — even the ones you don’t hear about. There’s a huge amount of high quality information out there which is just really hard to track.”
Saturday, 7 March 2015
Venture Capital Firm Formation 8 Dropped From Sexual Assault Lawsuit
The Apple Watch Is Time, SavedVenture capital firm Formation 8 has been removed as a defendant in a lawsuit filed in January against tech entrepreneur and investor Joe Lonsdale from a former girlfriend alleging sexual assault, battery, and other charges.
Lonsdale, who co-founded security and defense technology firm Palantir, is also a co-founder of Formation 8. He has vigorously denied all of Clougherty’s claims, and has characterized the suit as a “malicious campaign of lies.” He has countersued Clougherty for defamation.
Initially Formation 8 had been included as a defendant in the suit, which was first filed by plaintiff Elise Clougherty with the District Court in Northern California on January 27. Clougherty claimed that she had been an intern at Formation 8 during her relationship with Lonsdale, and that the firm was aware of the alleged abuse. The charge against Formation 8 was “negligent retention and supervision.”
However, on February 19, Formation 8’s attorneys filed a motion to dismiss Formation 8 from the suit based on several factors, including an expiration of the two year statute of limitations between the stated time of the alleged abuse and the filing of the claim. The motion also said that she never informed the firm of any alleged abuse at any time up until the suit. Also, the firm’s representatives have said that Clougherty was never on file as an employee or intern for Formation 8.
On March 5, Clougherty’s legal team responded by removing Formation 8 from the suit. “Although Plaintiff contests the representations in the Formation Defendants’ motion, Plaintiff believes that the case should move forward only against Defendant Lonsdale,” the filing says.
Lonsdale, who co-founded security and defense technology firm Palantir, is also a co-founder of Formation 8. He has vigorously denied all of Clougherty’s claims, and has characterized the suit as a “malicious campaign of lies.” He has countersued Clougherty for defamation.
Initially Formation 8 had been included as a defendant in the suit, which was first filed by plaintiff Elise Clougherty with the District Court in Northern California on January 27. Clougherty claimed that she had been an intern at Formation 8 during her relationship with Lonsdale, and that the firm was aware of the alleged abuse. The charge against Formation 8 was “negligent retention and supervision.”
However, on February 19, Formation 8’s attorneys filed a motion to dismiss Formation 8 from the suit based on several factors, including an expiration of the two year statute of limitations between the stated time of the alleged abuse and the filing of the claim. The motion also said that she never informed the firm of any alleged abuse at any time up until the suit. Also, the firm’s representatives have said that Clougherty was never on file as an employee or intern for Formation 8.
On March 5, Clougherty’s legal team responded by removing Formation 8 from the suit. “Although Plaintiff contests the representations in the Formation Defendants’ motion, Plaintiff believes that the case should move forward only against Defendant Lonsdale,” the filing says.
Tuesday, 24 February 2015
India’s HomeLane Raises $4.5M Series A Led By Sequoia Capital
Got a tip? Let us know.MenuSearchNewsChannelsStartupsMobileGadgetsEnterpriseSocialEuropeAsiaTrendingTinderNSAAndroidGoogleMicrosoftAppleTwitterFacebookAll TopicsAll GalleriesTCTVShowsTCTV NewsBuilt in BrooklynCrunchWeekFly Or DieGadgetsIncubatedInside JobsTC CribsAll ShowsAll VideosEventsTechSupport EventsDisruptStartup BattlefieldCrunchiesMeetupsInternational City EventsHackathonIncludeNews AboutGoogle I/O 2014CESSXSWWWDC 2014
Friday, 20 February 2015
Postmates Picks Up $35M In Series C From Spark Capital
Postmates, the on-demand delivery service that operates in nearly 60 markets, has raised $35 million in Series C exclusively from existing investor Spark Capital, according to our sources.
Postmates is a service that lets users order anything from local stores and have it delivered directly to their home for a small delivery fee.
The company launched back in 2011 and has raised a total of $58 million, including a $16 million Series B which was also led by Spark Capital with investments from Matrix Partners, SoftTech VC, Crosslink Capital, Scott Banister, Naval Ravikant, Russell Simmons, Thomas Korte, Shervin Pishevar, Dave Morin and David Sacks.
Sources tell TechCrunch that the latest deal, which valued the company between $150 million and $200 million, closed within the last month.
Postmates has made more than 1 million deliveries in nearly 60 markets across the United States, and has recently launched an API. Using the Postmates API, third-party sellers and app developers can offer same-day delivery powered by Postmates.
Scale is the most important factor in a business like Postmates, which generates a small amount of revenue per transaction, which is why it has been expanding so rapidly. This time last year, the company was only operating in four different markets.
There’s no doubt about the on-demand economy as a whole, with everyone from Amazon to Square to Uber to WunWun looking for a piece of the (on-demand) pie. But ultimately, the winner will be determined by who has the most surface area and the lowest prices.
Though Postmates seems to be expanding quickly (our office neighbor in SF, we often see them working late into the night), 2015 brings about its own significant hurdles.
Amazon recently turned on Prime Now, its one-hour delivery service, in New York, which may be one of the more valuable on-demand delivery markets in the country. Meanwhile, newer startups like WunWun (What U Want, When U Want) are operating under the same model, but undercutting Postmates’ pricing.
Postmates makes money by charging a delivery fee, which starts at $5 and escalates based on distance and
Saturday, 14 February 2015
August Capital Raises $450 Million For Its Seventh Fund, August VII
August Capital said today it has closed on $450 million for its latest venture capital fund, called August VII.
The new raise represents a downsizing of sorts for the 20-year-old Sand Hill Road firm. In 2012 August Capital raised $550 million for its sixth fund, August VI, and prior to that in 2009 raised $650 million for its fifth fund, August V.
In a blog post today, August Capital parter David Hornik explained that the smaller size was an intentional choice for the firm, bucking the larger industry trends of seemingly constant expansion to instead focus on quality over quantity. He wrote:
The new raise represents a downsizing of sorts for the 20-year-old Sand Hill Road firm. In 2012 August Capital raised $550 million for its sixth fund, August VI, and prior to that in 2009 raised $650 million for its fifth fund, August V.
In a blog post today, August Capital parter David Hornik explained that the smaller size was an intentional choice for the firm, bucking the larger industry trends of seemingly constant expansion to instead focus on quality over quantity. He wrote:
Wednesday, 11 February 2015
Capital Float, An Online Lending Platform For Indian Entrepreneurs, Scoops Up $13M From Sequoia and SAIF
Capital Float, a financial tech startup that wants to make it easier for small businesses in India to get loans, has raised a $13 million Series A led by SAIF Partners and Sequoia Capital. Existing investor Aspada also returned for the round.
Founded in 2013 and based in Bangalore with offices in New Delhi and Mumbai, Capital Float has raised a total of $17 million to date, all within the past twelve months. Capital Float will use its Series A to expand into more cities, improve its tech platform, and launch new products.
The company is also using its equity to finance loans, but plans to open up to other sources of capital by partnering with banks and individual investors. It makes money through a combination of interest and fees.
Surfing India’s E-Commerce Boom
So far, Capital Float has loaned more than $6 million to small businesses in 12 Indian cities. Its founders, Gaurav Hinduja and Sashank Rishyasringa, say the number of applications it processes increased by 10 times in 2014, with Capital Float now receiving about 200 loan requests per month.
Capital Float’s growth has been fueled mainly by India’s rapidly growing e-commerce market, which is expected to be worth $43 billion by the end of this decade. Seventy percent of its applicants are vendors who sell goods on marketplaces like Snapdeal, Flipkart, Amazon India, PayTM, or Myntra.
While e-commerce applicants are currently Capital Float’s largest vertical, the company also intends to launch products tailored to offline businesses, such as small manufacturers and business service providers.
About 20 percent to 30 percent of applicants are approved after the platform accesses their suitability based on 2,000 data points. In addition to the usual metrics, like credit bureau scores, Capital Float’s technology scores applications based on online data, including customer feedback and transaction history from online marketplaces. It also does psychometric assessments: in other words, applicants are asked questions to judge things like their ability to scale a business, attitude toward credit, and how they compare to competitors.
Capital Float’s use of data from online sources, including e-commerce marketplaces, is similar to the system developed by Alibaba affiliate Ant Financial for its new credit-scoring system, called Sesame Credit. Like Ant Financial, Capital Float is also tackling the problem of financing entrepreneurs in countries with fast-growing industries, such as e-commerce, that are underserved by traditional financial institutions.
Closing The Financing Gap
Hinduja and Rishyasringa said they became interested in financial tech while studying for their MBAs at the Stanford Graduate School of Business. They were intrigued by U.S. companies like Lending Club and On Deck, as well as Brazil’s NuBank (another Sequoia investment), and wanted to build a similar service in India.
Rishyasringa says that formal lending institutions in India provide $140 billion in loans to small businesses each year, but there is still a funding gap of $200 billion dollars. He adds that there are currently about 30 million small-to-medium businesses in India. Together they employ a total 69 million people and many are based in smaller cities, which Capital Float plans to expand into.
Founded in 2013 and based in Bangalore with offices in New Delhi and Mumbai, Capital Float has raised a total of $17 million to date, all within the past twelve months. Capital Float will use its Series A to expand into more cities, improve its tech platform, and launch new products.
The company is also using its equity to finance loans, but plans to open up to other sources of capital by partnering with banks and individual investors. It makes money through a combination of interest and fees.
Surfing India’s E-Commerce Boom
So far, Capital Float has loaned more than $6 million to small businesses in 12 Indian cities. Its founders, Gaurav Hinduja and Sashank Rishyasringa, say the number of applications it processes increased by 10 times in 2014, with Capital Float now receiving about 200 loan requests per month.
Capital Float’s growth has been fueled mainly by India’s rapidly growing e-commerce market, which is expected to be worth $43 billion by the end of this decade. Seventy percent of its applicants are vendors who sell goods on marketplaces like Snapdeal, Flipkart, Amazon India, PayTM, or Myntra.
While e-commerce applicants are currently Capital Float’s largest vertical, the company also intends to launch products tailored to offline businesses, such as small manufacturers and business service providers.
About 20 percent to 30 percent of applicants are approved after the platform accesses their suitability based on 2,000 data points. In addition to the usual metrics, like credit bureau scores, Capital Float’s technology scores applications based on online data, including customer feedback and transaction history from online marketplaces. It also does psychometric assessments: in other words, applicants are asked questions to judge things like their ability to scale a business, attitude toward credit, and how they compare to competitors.
Capital Float’s use of data from online sources, including e-commerce marketplaces, is similar to the system developed by Alibaba affiliate Ant Financial for its new credit-scoring system, called Sesame Credit. Like Ant Financial, Capital Float is also tackling the problem of financing entrepreneurs in countries with fast-growing industries, such as e-commerce, that are underserved by traditional financial institutions.
Closing The Financing Gap
Hinduja and Rishyasringa said they became interested in financial tech while studying for their MBAs at the Stanford Graduate School of Business. They were intrigued by U.S. companies like Lending Club and On Deck, as well as Brazil’s NuBank (another Sequoia investment), and wanted to build a similar service in India.
Rishyasringa says that formal lending institutions in India provide $140 billion in loans to small businesses each year, but there is still a funding gap of $200 billion dollars. He adds that there are currently about 30 million small-to-medium businesses in India. Together they employ a total 69 million people and many are based in smaller cities, which Capital Float plans to expand into.
Subscribe to:
Comments (Atom)
